





'''simple docstring'''






import logging
import os
from typing import List, TextIO, Union

from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask


A_		:  List[str]		 =						logging.getLogger(__name__)
class 					__snake_case  (					__SCREAMING_SNAKE_CASE							):






   '''simple docstring'''





   def __init__(							self	,		__SCREAMING_SNAKE_CASE=-1       ):
    # in NER datasets, the last column is usually reserved for NER label
    snake_case__     :					List[str]    =  label_idx

   def 		__UpperCamelCase						(							self	,		__SCREAMING_SNAKE_CASE	,		__SCREAMING_SNAKE_CASE       ):
    if isinstance(__SCREAMING_SNAKE_CASE	,		__SCREAMING_SNAKE_CASE       ):
     snake_case__     :					Any    =  mode.value
    snake_case__     :					List[str]    =  os.path.join(__SCREAMING_SNAKE_CASE	,		f"{mode}.txt"       )
    snake_case__     :					List[str]    =  1
    snake_case__     :					str    =  []
    with open(__SCREAMING_SNAKE_CASE	,		encoding="""utf-8"""       ) as f:
     snake_case__     :					Any    =  []
     snake_case__     :					Optional[Any]    =  []
     for line in f:
      if line.startswith("""-DOCSTART-"""       ) or line == "" or line == "\n":
       if words:
        examples.append(InputExample(guid=f"{mode}-{guid_index}"	,		words=__SCREAMING_SNAKE_CASE	,		labels=__SCREAMING_SNAKE_CASE       )       )
        guid_index += 1
        snake_case__     :					Any    =  []
        snake_case__     :					int    =  []
      else:
       snake_case__     :					Any    =  line.split(""" """       )
       words.append(splits[0]       )
       if len(__SCREAMING_SNAKE_CASE       ) > 1:
        labels.append(splits[self.label_idx].replace("""\n"""	,		""""""       )       )
       else:
        # Examples could have no label for mode = "test"
        labels.append("""O"""       )
     if words:
      examples.append(InputExample(guid=f"{mode}-{guid_index}"	,		words=__SCREAMING_SNAKE_CASE	,		labels=__SCREAMING_SNAKE_CASE       )       )
    return examples

   def 		__UpperCamelCase						(							self	,		__SCREAMING_SNAKE_CASE	,		__SCREAMING_SNAKE_CASE	,		__SCREAMING_SNAKE_CASE       ):
    snake_case__     :					Optional[int]    =  0
    for line in test_input_reader:
     if line.startswith("""-DOCSTART-"""       ) or line == "" or line == "\n":
      writer.write(__SCREAMING_SNAKE_CASE       )
      if not preds_list[example_id]:
       example_id += 1
     elif preds_list[example_id]:
      snake_case__     :					Any    =  line.split()[0] + """ """ + preds_list[example_id].pop(0       ) + """\n"""
      writer.write(__SCREAMING_SNAKE_CASE       )
     else:
      logger.warning("""Maximum sequence length exceeded: No prediction for '%s'."""	,		line.split()[0]       )


   def 		__UpperCamelCase						(							self	,		__SCREAMING_SNAKE_CASE       ):
    if path:
     with open(__SCREAMING_SNAKE_CASE	,		"""r"""       ) as f:
      snake_case__     :					List[Any]    =  f.read().splitlines()
     if "O" not in labels:
      snake_case__     :					Any    =  ["""O"""] + labels
     return labels
    else:
     return ["O", "B-MISC", "I-MISC", "B-PER", "I-PER", "B-ORG", "I-ORG", "B-LOC", "I-LOC"]



class 					__snake_case  (					__SCREAMING_SNAKE_CASE							):






   '''simple docstring'''





   def __init__(							self       ):
    # in CONLL2003 dataset chunk column is second-to-last
    super().__init__(label_idx=-2       )


   def 		__UpperCamelCase						(							self	,		__SCREAMING_SNAKE_CASE       ):
    if path:
     with open(__SCREAMING_SNAKE_CASE	,		"""r"""       ) as f:
      snake_case__     :					Optional[int]    =  f.read().splitlines()
     if "O" not in labels:
      snake_case__     :					List[Any]    =  ["""O"""] + labels
     return labels
    else:
     return [
         "O",
         "B-ADVP",
         "B-INTJ",
         "B-LST",
         "B-PRT",
         "B-NP",
         "B-SBAR",
         "B-VP",
         "B-ADJP",
         "B-CONJP",
         "B-PP",
         "I-ADVP",
         "I-INTJ",
         "I-LST",
         "I-PRT",
         "I-NP",
         "I-SBAR",
         "I-VP",
         "I-ADJP",
         "I-CONJP",
         "I-PP",
     ]



class 					__snake_case  (					__SCREAMING_SNAKE_CASE							):






   '''simple docstring'''





   def 		__UpperCamelCase						(							self	,		__SCREAMING_SNAKE_CASE	,		__SCREAMING_SNAKE_CASE       ):
    if isinstance(__SCREAMING_SNAKE_CASE	,		__SCREAMING_SNAKE_CASE       ):
     snake_case__     :					Optional[Any]    =  mode.value
    snake_case__     :					int    =  os.path.join(__SCREAMING_SNAKE_CASE	,		f"{mode}.txt"       )
    snake_case__     :					Union[str, Any]    =  1
    snake_case__     :					Any    =  []

    with open(__SCREAMING_SNAKE_CASE	,		encoding="""utf-8"""       ) as f:
     for sentence in parse_incr(__SCREAMING_SNAKE_CASE       ):
      snake_case__     :					Optional[Any]    =  []
      snake_case__     :					Optional[Any]    =  []
      for token in sentence:
       words.append(token["""form"""]       )
       labels.append(token["""upos"""]       )
      assert len(__SCREAMING_SNAKE_CASE       ) == len(__SCREAMING_SNAKE_CASE       )
      if words:
       examples.append(InputExample(guid=f"{mode}-{guid_index}"	,		words=__SCREAMING_SNAKE_CASE	,		labels=__SCREAMING_SNAKE_CASE       )       )
       guid_index += 1
    return examples

   def 		__UpperCamelCase						(							self	,		__SCREAMING_SNAKE_CASE	,		__SCREAMING_SNAKE_CASE	,		__SCREAMING_SNAKE_CASE       ):
    snake_case__     :					Tuple    =  0
    for sentence in parse_incr(__SCREAMING_SNAKE_CASE       ):
     snake_case__     :					int    =  preds_list[example_id]
     snake_case__     :					Any    =  """"""
     for token in sentence:
      out += f"{token['form']} ({token['upos']}|{s_p.pop(0       )}) "
     out += "\n"
     writer.write(__SCREAMING_SNAKE_CASE       )
     example_id += 1


   def 		__UpperCamelCase						(							self	,		__SCREAMING_SNAKE_CASE       ):
    if path:
     with open(__SCREAMING_SNAKE_CASE	,		"""r"""       ) as f:
      return f.read().splitlines()
    else:
     return [
         "ADJ",
         "ADP",
         "ADV",
         "AUX",
         "CCONJ",
         "DET",
         "INTJ",
         "NOUN",
         "NUM",
         "PART",
         "PRON",
         "PROPN",
         "PUNCT",
         "SCONJ",
         "SYM",
         "VERB",
         "X",
     ]










'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCAmelCase_					=   {
    "configuration_time_series_transformer": [
        "TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "TimeSeriesTransformerConfig",
    ],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase_					=   [
      "TIME_SERIES_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
      "TimeSeriesTransformerForPrediction",
      "TimeSeriesTransformerModel",
      "TimeSeriesTransformerPreTrainedModel",
  ]


if TYPE_CHECKING:
  from .configuration_time_series_transformer import (
      TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
      TimeSeriesTransformerConfig,
  )

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_time_series_transformer import (
        TIME_SERIES_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
        TimeSeriesTransformerForPrediction,
        TimeSeriesTransformerModel,
        TimeSeriesTransformerPreTrainedModel,
    )

else:
  import sys

  UpperCAmelCase_					=   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



